search

IntelPython / scikit-learn_bench

scikit-learn_bench benchmarks various implementations of machine learning algorithms across data analytics frameworks. It currently support the scikit-learn, DAAL4PY, cuML, and XGBoost frameworks for commonly used machine learning algorithms.
Apache License 2.0
111 stars 69 forks source link

xgboost benchmark datasets missing #117

Open xwu99 opened 2 years ago

xwu99 commented 2 years ago

When benchmark using xgb_cpu_main_config.json. The following datasets are missing

WARNING: Dataset mlsr could not be loaded.
Check the correct name or expand the download in the folder dataset.
INFO: gbt algorithm: 1 case(s), 1 dataset(s)

WARNING: Dataset mortgage1Q could not be loaded.
Check the correct name or expand the download in the folder dataset.
INFO: gbt algorithm: 1 case(s), 1 dataset(s)

WARNING: Dataset plasticc could not be loaded.
Check the correct name or expand the download in the folder dataset.
INFO: gbt algorithm: 1 case(s), 1 dataset(s)

WARNING: Dataset santander could not be loaded.
Check the correct name or expand the download in the folder dataset.
napetrov commented 1 year ago

i think this would be addressed as part of https://github.com/IntelPython/scikit-learn_bench/pull/133